Background: Malaria remains a major public-health challenge in sub-Saharan Africa, where transmission varies geographically and over time and is influenced by climatic, environmental, demographic and health-system factors. Objective: To map geospatial approaches used to describe and predict malaria transmission in sub-Saharan Africa, including predictors, modelling methods, early-warning applications and implications for malaria control. Methods: The manuscript was structured using the Population–Concept–Context framework and PRISMA-ScR guidance, with a planned evidence window of 2021–2025. The original database search exports and screening records were unavailable; a supplementary targeted public-web search was conducted on 17 October 2026 to verify selected studies and expand the evidence chart. This supplementary search did not generate a complete deduplicated record set, so PRISMA flow counts remain pending and have not been fabricated. Results: Verified candidate studies illustrate GIS hotspot analysis, remote sensing, Bayesian geostatistics, model-based geostatistics and spatiotemporal modelling in Ghana, Kenya, Ethiopia and Nigeria. Recurring predictors include rainfall, temperature, vegetation, aridity, land cover, intervention coverage and access to health services. Conclusion: Geospatial methods can support malaria risk stratification, but operational value depends on data quality, local validation, uncertainty reporting and translation of maps into public-health decisions. The manuscript requires complete database searches, formal screening, evidence charting and a final PRISMA-ScR flow diagram before it can be represented as a completed reproducible scoping review. Objective: This review synthesises recent evidence on how geospatial mapping and spatial modelling are being used to characterise and predict malaria transmission in sub-Saharan Africa, with particular attention to environmental and climatic predictors, modelling approaches,